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Reviewed 11 May 2026

Completeness Strong (72%)

Brain Health (Quantib® ND)

FDA

Brain Health (previously Saige Brain and Quantib® ND) offers automated segmentation of brain structures and white matter hyperintensities. This machine learning radiology application provides insight into the possible presence of atrophy related to Alzheimer's disease or other types of dementia. Brain Health's follow-up feature allows for tracking of neuro degeneration over time. Automatic assessment of white matter hyperintensity development supports monitoring of MS patients.The software distinguishes between new and previously identified WMHs, providing a visualization with color-coded lesions super positioned on an anatomical map.

Supported by 4 papers

Key Features

Brain structure segmentation and volume quantification
Comparison to reference population
Multiple time-point analysis
White matter hyperintensity detection and quantification

General Information

Product name

Brain Health (Quantib® ND)

Company

DeepHealth

Modality

Main task

Not specified

Subspeciality

Neuro

Disease targeted

Neurodegenerative diseases, dementia, Alzheimer’s disease, Multiple Sclerosis

Regulatory Information

CE Certification

Pathway:

MDR

Class:

Class IIa

Verified by Health AI Register

FDA Certification

Pathway:

510(k) cleared

Class:

Class II

Verified by Health AI Register

Other certifications

Not specified

Evidence & Research

Peer-Reviewed Papers

Automated MRI-based brain volumetric analysis in women with polycystic ovary syndrome

BMC Medical Imaging · Apr 2026

MRI approach to the patient with suspected dementia: artificial intelligence techniques and semi-quantitative rating scales compared

Frontiers in Radiology · Jan 2026

Combining semi-quantitative rating and automated brain volumetry in MRI evaluation of patients with probable behavioural variant of fronto-temporal dementia: an added value for clinical practise?

Neuroradiology · Mar 2023

Comparing two artificial intelligence software packages for normative brain volumetry in memory clinic imaging

Neuroradiology · Jan 2022

Technical Specifications

Patient population age

Not specified

Input

(contrast) 3DT1 MRI, (contrast) 3D or 2D T2 FLAIR MRI

Input format

DICOM

Output

segmentation overlays, draft radiology report including normative comparison

Output format

DICOM

Integration

Integration via AI marketplace or distribution platform, Stand-alone third party application

Deployment

Locally on dedicated hardware

Trigger for analysis

Automatically, right after the image acquisition, On demand, triggered by a user through e.g. a button click, image upload

Processing time

> 10 minutes

Population

All with suspicion of neuro degenerative disease, dementia, Alzheimer’s disease, MS

Market Presence

On market since

09-2017

AI Platforms

CARPL.AI

Resellers

Not specified

Countries present

Not specified

Paying clinical customers

Not specified

Research/test users

Not specified

Pricing Information

Pricing model

Subscription

Based on

Number of installations, Number of users

Source: Vendor | First published: Nov 30, 2023 | Last updated: May 11, 2026